The conventional system provides Reliability Block Diagrams (RDB) which is too simplistic with support for only binary states. These states don't adequately model the different states of a software component or system, like a state with reduced functionality. Also, modeling a complex software system with Markov Model results in a complex model with unmanageable number of states which is difficult to use for computations.
The present disclosure describes how to improve on existing Markov Models & Hidden Markov Models through the implementation of encapsulation using the process of decomposition of the software application into sub-units. This approach can be used for modeling the complete software application. The model achieved from this method is a combined result of many Markov Models or Hidden Markov Models at the sub-units level. Hence it is called a Composite Hidden Markov Model (CHMM) at the system level. It also explains how to combine the mathematical models with measured values and how to apply probability theory to solve the uncertainties in estimating availability of complex software systems.